nixpkgs/pkgs/development/python-modules/tensorflow/default.nix
Luke Granger-Brown d385b8f597 python3Packages.tensorflow: mark as requiring big-parallel
The Bazel build part of tensorflow builds can really use as many cores
as is available - to avoid blocking a small machine for literally hours
while it churns away, mark the build as big-parallel so we can schedule
it to run quickly on a machine with lots of cores.
2021-04-24 01:12:19 +00:00

427 lines
13 KiB
Nix

{ stdenv, bazel_3, buildBazelPackage, isPy3k, lib, fetchFromGitHub, symlinkJoin
, addOpenGLRunpath
# Python deps
, buildPythonPackage, pythonOlder, pythonAtLeast, python
# Python libraries
, numpy, tensorflow-tensorboard_2, absl-py
, future, setuptools, wheel, keras-preprocessing, google-pasta
, opt-einsum, astunparse, h5py
, termcolor, grpcio, six, wrapt, protobuf, tensorflow-estimator_2
, dill, flatbuffers-python, tblib, typing-extensions
# Common deps
, git, pybind11, which, binutils, glibcLocales, cython, perl
# Common libraries
, jemalloc, mpi, gast, grpc, sqlite, boringssl, jsoncpp
, curl, snappy, flatbuffers-core, lmdb-core, icu, double-conversion, libpng, libjpeg_turbo, giflib
# Upsteam by default includes cuda support since tensorflow 1.15. We could do
# that in nix as well. It would make some things easier and less confusing, but
# it would also make the default tensorflow package unfree. See
# https://groups.google.com/a/tensorflow.org/forum/#!topic/developers/iRCt5m4qUz0
, cudaSupport ? false, cudatoolkit ? null, cudnn ? null, nccl ? null
, mklSupport ? false, mkl ? null
, tensorboardSupport ? true
# XLA without CUDA is broken
, xlaSupport ? cudaSupport
# Default from ./configure script
, cudaCapabilities ? [ "sm_35" "sm_50" "sm_60" "sm_70" "sm_75" "compute_80" ]
, sse42Support ? stdenv.hostPlatform.sse4_2Support
, avx2Support ? stdenv.hostPlatform.avx2Support
, fmaSupport ? stdenv.hostPlatform.fmaSupport
# Darwin deps
, Foundation, Security
}:
assert cudaSupport -> cudatoolkit != null
&& cudnn != null;
# unsupported combination
assert ! (stdenv.isDarwin && cudaSupport);
assert mklSupport -> mkl != null;
let
withTensorboard = (pythonOlder "3.6") || tensorboardSupport;
cudatoolkit_joined = symlinkJoin {
name = "${cudatoolkit.name}-merged";
paths = [
cudatoolkit.lib
cudatoolkit.out
] ++ lib.optionals (lib.versionOlder cudatoolkit.version "11") [
# for some reason some of the required libs are in the targets/x86_64-linux
# directory; not sure why but this works around it
"${cudatoolkit}/targets/${stdenv.system}"
];
};
cudatoolkit_cc_joined = symlinkJoin {
name = "${cudatoolkit.cc.name}-merged";
paths = [
cudatoolkit.cc
binutils.bintools # for ar, dwp, nm, objcopy, objdump, strip
];
};
# Needed for _some_ system libraries, grep INCLUDEDIR.
includes_joined = symlinkJoin {
name = "tensorflow-deps-merged";
paths = [
jsoncpp
];
};
tfFeature = x: if x then "1" else "0";
version = "2.4.0";
variant = if cudaSupport then "-gpu" else "";
pname = "tensorflow${variant}";
pythonEnv = python.withPackages (_:
[ # python deps needed during wheel build time (not runtime, see the buildPythonPackage part for that)
# This list can likely be shortened, but each trial takes multiple hours so won't bother for now.
absl-py
astunparse
dill
flatbuffers-python
gast
google-pasta
grpcio
h5py
keras-preprocessing
numpy
opt-einsum
protobuf
setuptools
six
tblib
tensorflow-estimator_2
tensorflow-tensorboard_2
termcolor
typing-extensions
wheel
wrapt
]);
bazel-build = buildBazelPackage {
name = "${pname}-${version}";
bazel = bazel_3;
src = fetchFromGitHub {
owner = "tensorflow";
repo = "tensorflow";
rev = "v${version}";
sha256 = "0yl06aypfxrcs35828xf04mkidz1x0j89v0q5h4d2xps1cb5rv3f";
};
patches = [
# Relax too strict Python packages versions dependencies.
./relax-dependencies.patch
# Add missing `io_bazel_rules_docker` dependency.
./workspace.patch
];
# On update, it can be useful to steal the changes from gentoo
# https://gitweb.gentoo.org/repo/gentoo.git/tree/sci-libs/tensorflow
nativeBuildInputs = [
which pythonEnv cython perl
] ++ lib.optional cudaSupport addOpenGLRunpath;
buildInputs = [
jemalloc
mpi
glibcLocales
git
# libs taken from system through the TF_SYS_LIBS mechanism
grpc
sqlite
boringssl
jsoncpp
curl
pybind11
snappy
flatbuffers-core
icu
double-conversion
libpng
libjpeg_turbo
giflib
lmdb-core
] ++ lib.optionals cudaSupport [
cudatoolkit
cudnn
] ++ lib.optionals mklSupport [
mkl
] ++ lib.optionals stdenv.isDarwin [
Foundation
Security
];
# arbitrarily set to the current latest bazel version, overly careful
TF_IGNORE_MAX_BAZEL_VERSION = true;
# Take as many libraries from the system as possible. Keep in sync with
# list of valid syslibs in
# https://github.com/tensorflow/tensorflow/blob/master/third_party/systemlibs/syslibs_configure.bzl
TF_SYSTEM_LIBS = lib.concatStringsSep "," [
"absl_py"
"astor_archive"
"astunparse_archive"
"boringssl"
# Not packaged in nixpkgs
# "com_github_googleapis_googleapis"
# "com_github_googlecloudplatform_google_cloud_cpp"
"com_github_grpc_grpc"
# Multiple issues with custom protobuf.
# First `com_github_googleapis` fails to configure. Can be worked around by disabling `com_github_googleapis`
# and related functionality, but then the next error is about "dangling symbolic link", and in general
# looks like that's only the beginning: see
# https://stackoverflow.com/questions/55578884/how-to-build-tensorflow-1-13-1-with-custom-protobuf
# "com_google_protobuf"
# Fails with the error: external/org_tensorflow/tensorflow/core/profiler/utils/tf_op_utils.cc:46:49: error: no matching function for call to 're2::RE2::FullMatch(absl::lts_2020_02_25::string_view&, re2::RE2&)'
# "com_googlesource_code_re2"
"curl"
"cython"
"dill_archive"
"double_conversion"
"enum34_archive"
"flatbuffers"
"functools32_archive"
"gast_archive"
"gif"
"hwloc"
"icu"
"jsoncpp_git"
"libjpeg_turbo"
"lmdb"
"nasm"
# "nsync" # not packaged in nixpkgs
"opt_einsum_archive"
"org_sqlite"
"pasta"
"pcre"
"png"
"pybind11"
"six_archive"
"snappy"
"tblib_archive"
"termcolor_archive"
"typing_extensions_archive"
"wrapt"
"zlib"
];
INCLUDEDIR = "${includes_joined}/include";
PYTHON_BIN_PATH = pythonEnv.interpreter;
TF_NEED_GCP = true;
TF_NEED_HDFS = true;
TF_ENABLE_XLA = tfFeature xlaSupport;
CC_OPT_FLAGS = " ";
# https://github.com/tensorflow/tensorflow/issues/14454
TF_NEED_MPI = tfFeature cudaSupport;
TF_NEED_CUDA = tfFeature cudaSupport;
TF_CUDA_PATHS = lib.optionalString cudaSupport "${cudatoolkit_joined},${cudnn},${nccl}";
GCC_HOST_COMPILER_PREFIX = lib.optionalString cudaSupport "${cudatoolkit_cc_joined}/bin";
GCC_HOST_COMPILER_PATH = lib.optionalString cudaSupport "${cudatoolkit_cc_joined}/bin/gcc";
TF_CUDA_COMPUTE_CAPABILITIES = lib.concatStringsSep "," cudaCapabilities;
postPatch = ''
# bazel 3.3 should work just as well as bazel 3.1
rm -f .bazelversion
'' + lib.optionalString (!withTensorboard) ''
# Tensorboard pulls in a bunch of dependencies, some of which may
# include security vulnerabilities. So we make it optional.
# https://github.com/tensorflow/tensorflow/issues/20280#issuecomment-400230560
sed -i '/tensorboard ~=/d' tensorflow/tools/pip_package/setup.py
'';
# https://github.com/tensorflow/tensorflow/pull/39470
NIX_CFLAGS_COMPILE = [ "-Wno-stringop-truncation" ];
preConfigure = let
opt_flags = []
++ lib.optionals sse42Support ["-msse4.2"]
++ lib.optionals avx2Support ["-mavx2"]
++ lib.optionals fmaSupport ["-mfma"];
in ''
patchShebangs configure
# dummy ldconfig
mkdir dummy-ldconfig
echo "#!${stdenv.shell}" > dummy-ldconfig/ldconfig
chmod +x dummy-ldconfig/ldconfig
export PATH="$PWD/dummy-ldconfig:$PATH"
export PYTHON_LIB_PATH="$NIX_BUILD_TOP/site-packages"
export CC_OPT_FLAGS="${lib.concatStringsSep " " opt_flags}"
mkdir -p "$PYTHON_LIB_PATH"
# To avoid mixing Python 2 and Python 3
unset PYTHONPATH
'';
configurePhase = ''
runHook preConfigure
./configure
runHook postConfigure
'';
hardeningDisable = [ "format" ];
bazelBuildFlags = [
"--config=opt" # optimize using the flags set in the configure phase
]
++ lib.optionals (mklSupport) [ "--config=mkl" ];
bazelTarget = "//tensorflow/tools/pip_package:build_pip_package //tensorflow/tools/lib_package:libtensorflow";
removeRulesCC = false;
# Without this Bazel complaints about sandbox violations.
dontAddBazelOpts = true;
fetchAttrs = {
# cudaSupport causes fetch of ncclArchive, resulting in different hashes
sha256 = if cudaSupport then
"1i7z2a7bc2q1vn1h9nx1xc6g1r1cby2xvbcs20fj9h6c2fgaw9j4"
else
"0s8q5rxq8abr50c5jpwv96ncfc0k8jw7w70ri8viqy031g9v9v45";
};
buildAttrs = {
outputs = [ "out" "python" ];
preBuild = ''
patchShebangs .
'';
installPhase = ''
mkdir -p "$out"
tar -xf bazel-bin/tensorflow/tools/lib_package/libtensorflow.tar.gz -C "$out"
# Write pkgconfig file.
mkdir "$out/lib/pkgconfig"
cat > "$out/lib/pkgconfig/tensorflow.pc" << EOF
Name: TensorFlow
Version: ${version}
Description: Library for computation using data flow graphs for scalable machine learning
Requires:
Libs: -L$out/lib -ltensorflow
Cflags: -I$out/include/tensorflow
EOF
# build the source code, then copy it to $python (build_pip_package
# actually builds a symlink farm so we must dereference them).
bazel-bin/tensorflow/tools/pip_package/build_pip_package --src "$PWD/dist"
cp -Lr "$PWD/dist" "$python"
'';
postFixup = lib.optionalString cudaSupport ''
find $out -type f \( -name '*.so' -or -name '*.so.*' \) | while read lib; do
addOpenGLRunpath "$lib"
done
'';
requiredSystemFeatures = [
"big-parallel"
];
};
meta = with lib; {
description = "Computation using data flow graphs for scalable machine learning";
homepage = "http://tensorflow.org";
license = licenses.asl20;
maintainers = with maintainers; [ jyp abbradar ];
platforms = with platforms; linux ++ darwin;
broken = !(xlaSupport -> cudaSupport);
};
};
in buildPythonPackage {
inherit version pname;
disabled = !isPy3k;
src = bazel-build.python;
# Upstream has a pip hack that results in bin/tensorboard being in both tensorflow
# and the propagated input tensorflow-tensorboard, which causes environment collisions.
# Another possibility would be to have tensorboard only in the buildInputs
# https://github.com/tensorflow/tensorflow/blob/v1.7.1/tensorflow/tools/pip_package/setup.py#L79
postInstall = ''
rm $out/bin/tensorboard
'';
setupPyGlobalFlags = [ "--project_name ${pname}" ];
# tensorflow/tools/pip_package/setup.py
propagatedBuildInputs = [
absl-py
astunparse
dill
flatbuffers-python
gast
google-pasta
grpcio
h5py
keras-preprocessing
numpy
opt-einsum
protobuf
six
tblib
tensorflow-estimator_2
termcolor
typing-extensions
wrapt
] ++ lib.optionals withTensorboard [
tensorflow-tensorboard_2
];
nativeBuildInputs = lib.optional cudaSupport addOpenGLRunpath;
postFixup = lib.optionalString cudaSupport ''
find $out -type f \( -name '*.so' -or -name '*.so.*' \) | while read lib; do
addOpenGLRunpath "$lib"
patchelf --set-rpath "${cudatoolkit}/lib:${cudatoolkit.lib}/lib:${cudnn}/lib:${nccl}/lib:$(patchelf --print-rpath "$lib")" "$lib"
done
'';
# Actual tests are slow and impure.
# TODO try to run them anyway
# TODO better test (files in tensorflow/tools/ci_build/builds/*test)
checkPhase = ''
${python.interpreter} <<EOF
# A simple "Hello world"
import tensorflow as tf
hello = tf.constant("Hello, world!")
tf.print(hello)
# Fit a simple model to random data
import numpy as np
np.random.seed(0)
tf.random.set_seed(0)
model = tf.keras.models.Sequential([
tf.keras.layers.Dense(1, activation="linear")
])
model.compile(optimizer="sgd", loss="mse")
x = np.random.uniform(size=(1,1))
y = np.random.uniform(size=(1,))
model.fit(x, y, epochs=1)
EOF
'';
# Regression test for #77626 removed because not more `tensorflow.contrib`.
passthru = {
deps = bazel-build.deps;
libtensorflow = bazel-build.out;
};
inherit (bazel-build) meta;
}